Setting up Nvidia TX1 Dev board with JetPack 3.2 and SSD with a bonus

Tue Apr 10 2018

Disclaimer: This post is more or less a transcript of the videos by Jim from jetsonhacks.com.

I am a beginner to the world of machine learning and own a couple of Macbooks. I found the Nvidia Dev board (TX1) to be the best way to get started and run a few tensorflow / Cuda code on. Before I could do that, I had to make sure it was usable, and that was much more than I had bargained for.

Annoyingly, the Nvidia TX1 Dev board is not directly flashable via a usb stick. You need a host machine where you setup the dev board using the 'Force Recovery USB Mode'. You can find a video of setup using an older version of JetPack here.

To start the target setup, you need to connect the TX1, using the provided USB cord, to the host machine and switch to 'Force Recovery USB Mode'. The instructions for which are printed on the screen.

Caveat: The installation is usually smooth and if you see it hang near the line "Sending BCT..." or something similar, either change the port on your host machine or change the cord. I had it working using a different cord.

You should also connect your Board via ethernet port to a LAN, which the Host is connected to.

Press enter, once you are ready. Most probably everything will install smoothly, as it did in my case. You might lose wifi connectivity on the host (if using wifi) a couple of times. Don't worry, it happens. The most important thing is that the connection on the target is not flaky.

TX1 comes with a built in capacity of ~16 GB, out of which, the above installation takes about >8 GB. It leaves us with very little space to work with. One option was to install a SD card using the provided slot, I wanted much more. I wanted to run the OS on a ~256 GB SSD. You can follow the video, or read along.

I am a huge fan of containerization. I have see a lot of projects messing up an environment quickly because of conflicting dependencies. To counter that you can install docker using:

$ sudo apt-get install docker.io

It is as simple as that from 'Ubuntu 16.04' and 'JetPack 3.2' onwards. I haven't been able to find the device_query image which is referenced in this forum. Let me know, if you were able to get the following command working: